Bridging the Gap: How Nonprofits Are Navigating AI Adoption and Governance

The headline figure conceals the structural gap beneath it: 57% of executives report no dedicated AI budget for the technology, and 58% say no AI roadmap exists. Adoption has outrun governance.

The adoption profile

The report draws on 917 respondents surveyed between late April and mid-June. Official use — organized pilots, team-wide deployment, or fully integrated operations — sits at 61%. The breakdown: 33% in pilots, 24% team-wide, 4% fully integrated. Only 2% of respondents report no AI use at all. Frequency is high: 45% use AI for work at least daily; another 29% use it roughly once a week.

Five governance categories were weighed by respondents — AI-related budget, staff training, infrastructure (cloud storage, computing resources), data organization, and staff knowledge of responsible use. Budget is the widest gap. Training, infrastructure, and strategy lag alongside it. 37% of organizations do not currently train staff on AI tools. AI roadmaps are absent at 58% of organizations; only 8% have one in place. Written guidance is similarly thin: 40% have documented rules on what data can be used with AI, and 38% have written rules for responsible use. The report's authors observe that a meaningful share of sector-wide AI activity, including among executives, falls outside clearly defined guidance by default.

The funding profile

A second dataset — Fast Forward's 2026 AI for Humanity Report — covers 119 AI-powered nonprofits across 20 countries. The headline gap is execution capacity. 90% of organizations piloting or scaling AI have a plan to scale; only 24% report the resources to execute it. That 66-point gap is the sector's binding constraint.

Current spend remains modest. 61% of responding organizations spend less than $150,000 annually on AI, inclusive of tools, infrastructure, staff time, and contracts. The report flags this figure as a stage indicator rather than a true cost: early-stage organizations dominate the low-spend cohort. As AI becomes core infrastructure, spend rises sharply. 45% of respondents identify rising AI tools and infrastructure costs as their top external threat. 22% identify vendor or platform changes as a major external threat — a function of the sector's reliance on off-the-shelf models rather than internally built systems. Among organizations reporting increased reach, only 13% attribute the growth entirely to AI; most cite it as one factor among several.

What to verify

• Dedicated AI budget line item in current fiscal year financials.
• Existence of an AI policy document covering data inputs, responsible use, and vendor review.
• Staff training schedule for AI tools, with completion tracked.
• AI roadmap status: absent, in development, or active.
• Annual AI spend, broken down by tools, infrastructure, staff time, contracts.
• Vendor concentration risk: percentage of AI capability dependent on a single platform.